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Title

Discovering the role of temporal features in flies’ olfactory navigation using optogenetics

Mentor

Floris van Breugel, Ph.D.

Department

Mechanical Engineering

Biosketch

Floris van Breugel, Ph.D., earned his doctorate degree from Caltech in 2014 in control and dynamical systems under the support of NSF and Hertz graduate fellowships while working with Michael H. Dickinson on insect flight biomechanics, control, and multi-sensory integration. He subsequently went to the University of Washington to work with Jeff Riffell and J. Nathan Kutz as a postdoc to work on insect search strategies and machine learning approaches to system identification of complex systems, supported by a Sackler Fellowship in Biophysics and a Moore-Sloan-WRF Fellowship in DataScience. Floris joined the Department of Mechanical Engineering at the ÍƼöÐÓ°ÉÔ­´´ in January 2019. 

Project overview

Students interested in behavior and neuroscience can participate in a project aimed at discovering how fruit flies, Drosophila, navigate towards the source of an odor plume. A critical component of olfactory navigation is to determine the direction of ambient wind, as this is typically the best indicator of where the source of an attractive odor may be. Our group is working on discovering the neural circuits and behavioral motifs that contribute to flies ability to determine wind direction both in flight and while walking. To do this, we use a tool called optogenetics, which allows us to remotely turn on specific neurons in a genetically modified fly’s brain using light to simulate a fictive odor. Meanwhile, we can silence or kill other specific neurons in the brain to see if they are involved in the wind orientation behavior. PREP students would learn how to take care of the flies, use crosses to build the appropriate genotypes, run experiments, and analyze data. 

Students interested in applied robotics can participate in a project that aims to develop resilient estimation strategies for autonomous drones, partially inspired by how insects move and process information. Our lab has developed a control- and information-theoretic framework that enhances our ability to take advantage of sensory information during active movements. We are now working on using this framework to build state estimators that are robust to faulty sensors and demonstrate this principle on palm sized flying quadrotors. PREP students would learn to program the palm sized quadrotors and fly them in our indoor drone flight space to test algorithms that graduate students and postdocs in the lab have been developing. Students would learn to analyze the resulting data and assess the performance of different algorithmic approaches.

Pack Research Experience Program information and application